Azure Databricks Data Engineer

Job Overview:

• We are in search of a driven Databricks Data Engineer to architect, develop, and enhance state-of-the-art data platforms utilizing Databricks alongside cloud technologies.
• The successful candidate will possess direct experience in constructing extensive data pipelines, executing Lakehouse architectures, and facilitating advanced analytics solutions through Databricks Spark and related cloud environments.
• In this position, you will collaborate closely with data architects, analysts, business stakeholders, and engineering teams to create scalable, high-performance data solutions that drive enterprise-wide digital transformation initiatives.

Primary Duties:

• Design, develop, and sustain scalable data pipelines utilizing Databricks and Apache Spark.
• Construct and enhance ETL/ELT workflows for handling large-scale structured and unstructured data sets.
• Create data ingestion frameworks to assimilate data from a variety of sources, including databases, APIs, applications, and cloud storage.
• Execute and oversee Lakehouse architecture employing Databricks and Delta Lake.
• Enhance Spark jobs and Databricks workloads to ensure performance, scalability, and cost-effectiveness.
• Work in partnership with analytics, BI, and business teams to comprehend data requirements and deliver reusable data assets.
• Establish data quality frameworks, monitoring solutions, and governance controls throughout data pipelines.
• Diagnose production issues and offer prompt resolutions to maintain business continuity.
• Engage in architecture reviews, code assessments, and technical discussions to advocate for best practices.
• Generate and uphold technical documentation, reusable components, and deployment standards.

Technical Qualifications:

• 9 to 11 years of substantial hands-on experience with Databricks.
• Expertise in PySpark or Spark SQL for distributed data processing.
• Strong SQL capabilities with experience in query optimization and performance enhancement.
• Experience in designing and implementing ETL/ELT pipelines.
• Practical experience with Delta Lake, DataFrames, and Spark architecture.
• Understanding of data warehousing principles, dimensional modeling, and data lake architectures.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Familiarity with Git-based source code management and DevOps methodologies.
• Excellent analytical, debugging, and problem-solving capabilities.

Additional Responsibilities:

• The Infosys Data Analytics practice assists organizations in modernizing their data environments through cloud-native architectures, advanced analytics, AI, and intelligent data platforms.
• As a Databricks Data Engineer, you will engage in enterprise-level data modernization initiatives encompassing Lakehouse implementations, cloud migrations, real-time analytics, and AI-ready data ecosystems.

Desired Skills:

Technology->Data Engineering->Databricks